I have a df that I scraped from coinmarketcap. I am trying to calculate volitlity metrics for the close_price column but when I use a groupby I'm getting an error message:
final_coin_data['vol'] = final_coin_data.groupby('coin_name')['close_price'].rolling(window=30).std()
TypeError: incompatible index of inserted column with frame index
df structure (the 'Unnamed:0' came after I loaded my CSV):
Unnamed: 0 close_price coin_name date high_price low_price market_cap open_price volume
0 1 9578.63 Bitcoin Mar 11, 2018 9711.89 8607.12 149,716,000,000 8852.78 6,296,370,000
1 2 8866.00 Bitcoin Mar 10, 2018 9531.32 8828.47 158,119,000,000 9350.59 5,386,320,000
2 3 9337.55 Bitcoin Mar 09, 2018 9466.35 8513.03 159,185,000,000 9414.69 8,704,190,000
3 1 9578.63 Monero Mar 11, 2018 9711.89 8607.12 149,716,000,000 8852.78 6,296,370,000
4 2 8866.00 Monero Mar 10, 2018 9531.32 8828.47 158,119,000,000 9350.59 5,386,320,000
5 3 9337.55 Monero Mar 09, 2018 9466.35 8513.03 159,185,000,000 9414.69 8,704,190,000
(ignore the incorrect prices, this is the basics of the df)
When using the following code:
final_coin_data1['vol'] = final_coin_data.groupby('coin_name')['close_price'].rolling(window=30).std().reset_index(0,drop=True)
I got a MemoryError. I thought I was using groupby correctly. If I take out the final_coin_data1['vol'] =
then I get a series which appears correct, but it won't let me insert back into the df.
When I first started this project. I had just 1 coin and used the code below and it calculated volatility no problem.
final_coin_data1['vol'] = final_coin_data['close_price'].rolling(window=30).std()